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Model Development and Optimization for Space Engineering: Concepts, Tools, Applications, and Perspectives

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Modeling and Optimization in Space Engineering

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 73))

Abstract

The theory and methodology of finding the best possible solution to a broad range of optimization problems has been of interest since the beginnings of modern operations research. The key theoretical results regarding important model types and algorithmic frameworks have been followed by optimization software implementations that are used to handle a large and still growing variety of applications. Our discussion is focused on the practice of nonlinear—specifically including also global and mixed integer optimization, in the context of space engineering applications. We review some of the prominent solution approaches, model development tools, and software implementations of optimization (solver) engines and then relate our discussion to selected applications in space engineering. The review portion of this work cites contributions by our coauthors to the present volume (Fasano and Pintér, Modeling and Optimization in Space Engineering, Springer Science + Business Media, New York, 2012) while also drawing on an extensive list of other sources.

MSC Classification (2000) 68 T20, 90 C11, 90 C30, 90 C59, 90 C90, 90-02, 90-08

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References

  1. Schittkowski, K.: Numerical Data Fitting in Dynamical Systems. Kluwer, Dordrecht (2002)

    MATH  Google Scholar 

  2. Pintér, J.D.: Global Optimization in Action. Kluwer, Dordrecht (1996)

    MATH  Google Scholar 

  3. Pintér, J.D.: Globally optimized calibration of nonlinear models: techniques, software, and applications. Optim. Method. Softw. 18, 335–355 (2003)

    MATH  Google Scholar 

  4. Pintér, J.D.: Calibrating artificial neural networks by global optimization. Expert Syst. Appl. 39, 25–32 (2012)

    Google Scholar 

  5. Pintér, J.D.: Globally optimized spherical point arrangements: model variants and illustrative results. Ann. Oper. Res. 104, 213–230 (2001)

    MathSciNet  MATH  Google Scholar 

  6. Pintér, J.D., Kampas, F.J.: Nonlinear optimization in Mathematica with MathOptimizer Professional. Mathematica Educ. Res. 10, 1–18 (2005)

    Google Scholar 

  7. Pintér, J.D., Kampas, F.J.: Benchmarking nonlinear optimization software in technical computing environments: global optimization in Mathematica with MathOptimizer Professional. TOP (Off. J. Spanish Soc. Stat. Oper. Res.). Published online August 11 (2011). Doi: 10.1007/s11750-011-0209-5

  8. Castillo, I., Kampas, F.J., Pintér, J.D.: Solving circle packing problems by global optimization: numerical results and industrial applications. Eur. J. Oper. Res. 191, 786–802 (2008)

    MATH  Google Scholar 

  9. Fasano, G., Pintér, J.D.: Global optimization approaches to sensor placement: model versions and illustrative results. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013b)

    Google Scholar 

  10. Ciriani, T.A., Fasano, G., Gliozzi, S., Tadei, R. (eds.): Operations Research in Space and Air. Kluwer, Dordrecht (2003)

    MATH  Google Scholar 

  11. Fasano, G., Pintér, J.D. (eds.): Modeling and Optimization in Space Engineering. Springer, New York (2013a)

    Google Scholar 

  12. Bazaraa, M.S., Sherali, H.D., Shetty, C.M.: Nonlinear Programming: Theory and Algorithms. Wiley, New York (1993)

    MATH  Google Scholar 

  13. Peressini, A.L., Sullivan, F.E., Uhl, J.J.: The Mathematics of Nonlinear Programming. Springer, New York (1988)

    MATH  Google Scholar 

  14. Chong, E.K.P., Zak, S.H.: An Introduction to Optimization, 2nd edn. Wiley, New York (2001)

    MATH  Google Scholar 

  15. Edgar, T.F., Himmelblau, D.M., Lasdon, L.S.: Optimization of Chemical Processes, 2nd edn. McGraw-Hill, New York (2001)

    Google Scholar 

  16. Diwekar, U.: Introduction to Applied Optimization. Kluwer, Dordrecht (2003)

    MATH  Google Scholar 

  17. Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)

    MATH  Google Scholar 

  18. Hillier, F.J., Lieberman, G.J.: Introduction to Operations Research, 8th edn. McGraw-Hill, New York (2005)

    Google Scholar 

  19. Nocedal, J., Wright, S.J.: Numerical Optimization, 2nd edn. Springer, New York (2006)

    MATH  Google Scholar 

  20. Horst, R., Pardalos, P.M. (eds.): Handbook of Global Optimization, vol. 1. Kluwer, Dordrecht (1995)

    MATH  Google Scholar 

  21. Horst, R., Tuy, H.: Global Optimization: Deterministic Approaches. Springer, Berlin (1996)

    MATH  Google Scholar 

  22. Kearfott, R.B.: Rigorous Global Search: Continuous Problems. Kluwer, Dordrecht (1996)

    MATH  Google Scholar 

  23. Mockus, J., Eddy, W., Mockus, A., Mockus, L., Reklaitis, G.: Bayesian Heuristic Approach to Discrete and Global Optimization. Kluwer, Dordrecht (1996)

    Google Scholar 

  24. Floudas, C.A., Pardalos, P.M., Adjiman, C., Esposito, W.R., Gümüş, Z.H., Harding, S.T., Klepeis, J.L., Meyer, C.A., Schweiger, C.A.: Handbook of Test Problems in Local and Global Optimization. Kluwer, Dordrecht (1999)

    MATH  Google Scholar 

  25. Strongin, R.G., Sergeyev, Y.D.: Global Optimization with Non-Convex Constraints. Kluwer, Dordrecht (2000)

    MATH  Google Scholar 

  26. Pardalos, P.M., Romeijn, H.E. (eds.): Handbook of Global Optimization, vol. 2. Kluwer, Dordrecht (2002)

    MATH  Google Scholar 

  27. Zabinsky, Z.B.: Stochastic Adaptive Search for Global Optimization. Kluwer, Dordrecht (2003)

    MATH  Google Scholar 

  28. Liberti, L., Maculan, N. (eds.): Global Optimization: From Theory to Implementation. Springer, New York (2005)

    Google Scholar 

  29. Grossmann, I.E. (ed.): Global Optimization in Engineering Design. Kluwer, Dordrecht (1996)

    MATH  Google Scholar 

  30. Papalambros, P.Y., Wilde, D.J.: Principles of Optimal Design, 2nd edn. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  31. Pintér, J.D. (ed.): Global Optimization: Scientific and Engineering Case Studies. Springer, New York (2006)

    MATH  Google Scholar 

  32. Neumaier, A.: Complete search in continuous global optimization and constraint satisfaction. In: Iserles, A. (ed.) Acta Numerica 2004, pp. 271–369. Cambridge University Press, Cambridge (2004)

    Google Scholar 

  33. Floudas, C.A., Gounaris, C.E.: A review of recent advances in global optimization. J. Global Optim. 45, 3–38 (2009)

    MathSciNet  MATH  Google Scholar 

  34. Pintér, J.D.: Global optimization: software, test problems, and applications. In: Pardalos, P.M., Romeijn, H.E. (eds.) Handbook of Global Optimization, vol. 2, pp. 515–569. Kluwer, Dordrecht (2002)

    Google Scholar 

  35. Pintér, J.D.: Nonlinear optimization in modeling environments: software implementations for compilers, spreadsheets, modeling languages, and integrated computing systems. In: Jeyakumar, V., Rubinov, A.M. (eds.) Continuous Optimization: Current Trends and Modern Applications, pp. 147–173. Springer, New York (2005)

    Google Scholar 

  36. Rios, L.M., Sahinidis, N.V.: Derivative-free optimization: a review of algorithms and comparison of software implementations. Technical report, Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh (to appear)

    Google Scholar 

  37. Floudas, C.A.: Deterministic Global Optimization: Theory, Methods, and Applications. Kluwer, Dordrecht (2000)

    Google Scholar 

  38. Nowak, I.: Relaxation and Decomposition Methods for Mixed Integer Nonlinear Programming. Springer, New York (2005)

    MATH  Google Scholar 

  39. Tawarmalani, M., Sahinidis, N.V.: Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming. Kluwer, Dordrecht (2002)

    MATH  Google Scholar 

  40. Li, D., Sun, X.: Nonlinear Integer Programming. Springer, New York (2006)

    MATH  Google Scholar 

  41. Burer, S., Letchford, A.N.: Non-convex mixed-integer nonlinear programming: a survey. Technical Report, Department of Management Sciences, University of Iowa. http://www.optimization-online.org/DB_HTML/2012/02/3378.html (2012). Accessed on April 30, 2012

  42. Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs, 3rd edn. Springer, New York (1996)

    MATH  Google Scholar 

  43. Osman, I.H., Kelly, J.P. (eds.): Meta-Heuristics: Theory and Applications. Kluwer, Dordrecht (1996)

    MATH  Google Scholar 

  44. Glover, F., Laguna, M.: Tabu Search. Kluwer, Dordrecht (1997)

    MATH  Google Scholar 

  45. Rudolph, G.: Convergence Properties of Evolutionary Algorithms. Verlag Dr. Kovac, Hamburg (1997)

    Google Scholar 

  46. Voss, S., Martello, S., Osman, I.H., Roucairol, C. (eds.): Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization. Kluwer, Dordrecht (1999)

    MATH  Google Scholar 

  47. Rothlauf, F.: Representations for Genetic and Evolutionary Algorithms. Physica-Verlag, Heidelberg (2002)

    MATH  Google Scholar 

  48. Jones, N.C., Pevzner, P.A.: An Introduction to Bioinformatics Algorithms. MIT, Cambridge (2004)

    Google Scholar 

  49. Michalewicz, Z., Vogel, D.B.: How to Solve It: Modern Heuristics, 2nd edn. Springer, New York (2004)

    MATH  Google Scholar 

  50. Weise, T.: Global Optimization Algorithms—Theory and Application. An electronic book available for download at http://www.it-weise.de/projects/book.pdf (2009)

  51. Leyffer, S., Mahajan, A.: Software for nonlinearly constrained optimization. Preprint ANL/MCS-P1768-0610, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne (2010)

    Google Scholar 

  52. Pintér, J.D.: Software development for global optimization. In: Pardalos, P.M., Coleman, T.F. (eds.) Global Optimization: Methods and Applications. Fields Institute Communications, vol. 55, pp. 183–204. American Mathematical Society, Providence (2009)

    Google Scholar 

  53. Kallrath, J. (ed.): Modeling Languages in Mathematical Optimization. Kluwer, Dordrecht (2004)

    MATH  Google Scholar 

  54. Maplesoft: Maple. Maplesoft, Waterloo (2012). www.maplesoft.com

    Google Scholar 

  55. Wolfram Research: Mathematica. Wolfram Research, Champaign (2012). www.wolfram.com

    Google Scholar 

  56. The MathWorks: MATLAB. The MathWorks, Natick (2012). www.mathworks.com

    Google Scholar 

  57. Pintér, J.D.: LGO—A program system for continuous and Lipschitz optimization. In: Bomze, I.M., Csendes, T., Horst, R., Pardalos, P.M. (eds.) Developments in Global Optimization, pp. 183–197. Kluwer, Dordrecht (1997)

    Google Scholar 

  58. Pintér, J.D.: Nonlinear optimization with GAMS /LGO. J. Global Optim. 38, 79–101 (2007)

    MathSciNet  MATH  Google Scholar 

  59. Pintér, J.D., Kampas, F.J.: O.R. model development and optimization with Mathematica. In: Golden, B., Raghavan, S., Wasil, E. (eds.) The Next Wave in Computing, Optimization, and Decision Technologies, pp. 285–302. Springer, New York (2005)

    Google Scholar 

  60. Pintér, J.D., Linder, D., Chin, P.: Global optimization toolbox for maple: an introduction with illustrative applications. Optim. Method. Softw. 21(4), 565–582 (2006)

    MATH  Google Scholar 

  61. Pintér Consulting Services: LGO—A model development and solver system for global–local nonlinear optimization. User’s guide. Distributed by Pintér Consulting Services, Halifax (2012). www.pinterconsulting.com

    Google Scholar 

  62. Pintér, J.D.: RSS + LGO − a regularly spaced sampling method for experimental design integrated with the LGO solver suite for nonlinear optimization. Project report, TÁMOP 4.2.2-08/01-2008-0021 Project. Széchenyi István University, Győr (2011)

    Google Scholar 

  63. Pintér, J.D., Horváth, Z.: Integrated experimental design and nonlinear optimization to handle computationally expensive models under resource constraints. J. Global Optim. Published online March 15 (2012). doi: 10.1007/s10898-012-9882-7 (2012)

  64. Lahey Computer Systems: FORTRAN 95 User’s Guide. Lahey Computer Systems, Incline Village (2002). www.lahey.com

    Google Scholar 

  65. Lahey Computer Systems: FORTRAN 95 Language Reference. Lahey Computer Systems, Incline Village (2002). www.lahey.com

    Google Scholar 

  66. INFORMS Computing Society. Mathematical Programming Glossary. http://glossary.computing.society.informs.org/ (2012)

  67. Becerra, V.M.: Optimal control. Scholarpedia 3(1), 5354 (2008)

    Google Scholar 

  68. Becerra, V.M.: Solving optimal control problems at no cost with PSOPT. In: Proceedings of IEEE Multiconference on Systems and Control, Yokohama, Japan, 7–10 Sept 2010

    Google Scholar 

  69. Betts, J.T.: Practical Methods for Optimal Control Using Nonlinear Programming. SIAM, Philadelphia (2001)

    MATH  Google Scholar 

  70. Betts, J.T.: Practical Methods for Optimal Control and Estimation Using Nonlinear Programming. SIAM, Philadelphia (2010)

    MATH  Google Scholar 

  71. Büskens, C., Maurer, H.: SQP-methods for solving optimal control problems with control and state constraints: adjoint variables, sensitivity analysis and real-time control. J. Comput. Appl. Math. 120, 85–108 (2000)

    MathSciNet  MATH  Google Scholar 

  72. Elnagar, G., Kazemi, M.A., Razzaghi, M.: The pseudospectral Legendre method for discretizing optimal control problems. IEEE T. Automat. Contr. 40, 1793–1796 (1995)

    MathSciNet  MATH  Google Scholar 

  73. Hager, W.: Runge–Kutta methods in optimal control and the transformed adjoint system. Numer. Math. 87, 247–282 (2000)

    MathSciNet  MATH  Google Scholar 

  74. Halloin, H., Bastie, P.: Laue diffraction lenses for astrophysics: theoretical concepts. Exp. Astron. 20, 151–170 (2005)

    Google Scholar 

  75. Hartl, R.F., Sethi, S.P., Vickson, R.G.A.: A survey of the maximum principles for optimal control problems with state constraints. SIAM Rev. 37(2), 181–218 (1995)

    MathSciNet  MATH  Google Scholar 

  76. Kirk, D.E.: Optimal Control Theory: An Introduction. Dover, Mineola (2004)

    Google Scholar 

  77. Lebedev, L.P., Cloud, M.J.: The Calculus of Variations and Functional Analysis with Optimal Control and Applications in Mechanics. World Scientific, Singapore (2003)

    MATH  Google Scholar 

  78. Lewis, F.L., Syrmos, V.L.: Optimal Control, 2nd edn. Wiley, New York (1995)

    Google Scholar 

  79. Ross, I.M.: A primer on pontryagin's principle in optimal control. Collegiate Publishers, Carmel (2009)

    Google Scholar 

  80. Sethi, S., Thompson, G.: Optimal Control Theory: Applications to Management Science and Economics. Kluwer, Norwell (2000)

    MATH  Google Scholar 

  81. GTOC2: 2nd Global Trajectory Optimization Competition. http://www.esa.int/gsp/ACT/mad/op/GTOC/index.htm (2006). Accessed on April 30, 2012

  82. Becerra, V.M.: Practical direct collocation methods for computational optimal control. In: Fasano, G. Pintér, J.D., (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  83. Cassioli, A., Izzo, D., Di Lorenzo, D., Locatelli, M., Schoen, F.: Global optimization approaches for optimal trajectory planning. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  84. Colasurdo, G., Casalino, L.: Indirect methods for the optimization of spacecraft trajectories. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  85. Topputo, F., Belbruno, E.: Optimization of low energy transfers. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  86. Di Lizia, P., Armellin, R., Topputo, F., Bernelli-Zazzera, F., Berz, M.: Global optimization of interplanetary transfers with deep space maneuvers using differential algebra. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  87. Cremaschi, F.: Trajectory optimization for launchers and re-entry vehicles. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  88. Kampas, F.J., Pintér, J.D.: Solving a System of ODEs by the “Shooting Method”. An Illustrative Application of MathOptimizer Professional described in the User’s Guide. Pintér Consulting Services, Canada (2007). www.pinterconsulting.com

    Google Scholar 

  89. Büskens, C., Wassel, D.: The ESA NLP solver WORHP. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  90. Gabrel, V., Murat, C.: Mathematical programming for earth observation satellite mission planning. In: Ciriani, T., Fasano, G., Gliozzi, S., Tadei, R. (eds.) Operations Research in Space and Air, pp. 103–122. Kluwer, Dordrecht (2003)

    Google Scholar 

  91. Gürtuna, O., Trépanier, J.: On-orbit satellite servicing: a space-based vehicle routing problem. In: Ciriani, T., Fasano, G., Gliozzi, S., Tadei, R. (eds.) Operations Research in Space and Air, pp. 123–142. Kluwer, Dordrecht (2003)

    Google Scholar 

  92. Lang, D.E.: Launch capacity analysis for commercial communications satellites. In: Ciriani, T., Fasano, G., Gliozzi, S., Tadei, R. (eds.) Operations Research in Space and Air, pp. 161–178. Kluwer, Dordrecht (2003)

    Google Scholar 

  93. Fasano, G.: A global optimization point of view to handle non-standard object packing problems. J. Global Optim. (2012). DOI: 10.1007/s10898-012-9865-8 (to appear)

    Google Scholar 

  94. Fasano, G.: A traffic model for the international space station: an MIP approach. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  95. Fasano, G., Piras, A.: Mission integration optimization techniques in support of timelining, operational sequence definition and resource exploitation. In: Proceedings of the 23rd AIDAA (Italian Association of Aeronautics and Astronautics) Conference, Rome, Italy, 11–15 Sept 1995

    Google Scholar 

  96. Padberg, M.W., Rinaldi, G.: A branch and cut algorithm for the resolution of large-scale symmetric traveling salesman problems. SIAM Rev. 33, 60–100 (1991)

    MathSciNet  MATH  Google Scholar 

  97. Williams, H.P.: Model Building in Mathematical Programming, 4th edn. Wiley, Chichester (2000)

    Google Scholar 

  98. Cagan, J., Shimada, K., Yin, S.: A survey of computational approaches to three-dimensional layout problems. Comput. Aided Des. 34, 597–611 (2002)

    Google Scholar 

  99. Dyckhoff, H., Scheithauer, G., Terno, J.: Cutting and packing. In: Dell'Amico, M., Maffioli, F., Martello, S. (eds.) Annotated Bibliographies in Combinatorial Optimization, pp. 393–412. Wiley, Chichester (1997)

    Google Scholar 

  100. Fekete, S., Schepers, J.: A combinatorial characterization of higher-dimensional orthogonal packing. Math. Oper. Res. 29, 353–368 (2004)

    MathSciNet  MATH  Google Scholar 

  101. Faroe, O., Pisinger, D., Zachariasen, M.: Guided local search for the three-dimensional bin packing problem. INFORMS J. Comput. 15(3), 267–283 (2003)

    MathSciNet  MATH  Google Scholar 

  102. Martello, S., Pisinger, D., Vigo, D.: The three-dimensional bin packing problem. Oper. Res. 48(256), 267 (2000)

    MathSciNet  Google Scholar 

  103. Martello, S., Pisinger, D., Vigo, D., Den Boef, E., Korst, J.: Algorithm 864: general and robot-packable variants of the three-dimensional bin packing problem. ACM T. Math. Softw. 33(1) (2007)

    Google Scholar 

  104. Pisinger, D., Sigurd, M.M.: The two-dimensional bin packing problem with variable bin sizes and costs. Discrete Optim. 2(2), 154–167 (2005)

    MathSciNet  MATH  Google Scholar 

  105. Pisinger, D., Sigurd, M.M.: Using decomposition techniques and constraints programming for solving the two-dimensional bin packing problem. INFORMS J. Comput. 19(1), 36–51 (2006)

    MathSciNet  Google Scholar 

  106. Dowsland, K.A., Dowsland, W.B., Bennell, J.A.: Jostling for position: local improvement for irregular cutting patterns. J. Oper. Res. Soc. 49, 647–658 (1998)

    MATH  Google Scholar 

  107. Egeblad, J., Nielsen, B.K., Odgaard, A.: Fast neighbourhood search for two- and three-dimensional nesting problems. Eur. J. Oper. Res. 183(3), 1249–1266 (2007)

    MathSciNet  MATH  Google Scholar 

  108. Egeblad, J., Pisinger, D.: Heuristic approaches for the two- and three-dimensional knapsack packing problem. Comput. Oper. Res. 36, 1026–1049 (2009)

    MathSciNet  MATH  Google Scholar 

  109. Fischetti, M., Luzzi, I.: Mixed-integer programming models for nesting problems. J. Heuristics 15(3), 201–226 (2009)

    MATH  Google Scholar 

  110. Gomes, A.M., Oliveira, J.F.: A 2-exchange heuristics for nesting problems. Eur. J. Oper. Res. 141, 359–570 (2002)

    MathSciNet  MATH  Google Scholar 

  111. Ibaraki, T., Imahori, S., Yagiura, M.: Hybrid metaheuristics for packing problems. In: Blum, C., Blesa Aguilera, M.J., Roli, A., Sampels, M. (eds.) Hybrid Metaheuristics: An Emerging Approach to Optimization. Studies in Computational Intelligence (SCI), vol. 114, pp. 185–219. Springer, Berlin (2008)

    Google Scholar 

  112. Kallrath, J.: Cutting circles and polygons from area-minimizing rectangles. J. Global Optim. 43, 299–328 (2009)

    MathSciNet  MATH  Google Scholar 

  113. Scheithauer, G., Stoyan, Y.G., Romanova, T.Y.: Mathematical modeling of interactions of primary geometric 3D objects. Cybernet. Systems Anal. 41, 332–342 (2005)

    MathSciNet  MATH  Google Scholar 

  114. Stoyan, Y.G., Scheithauer, G., Gil, N., Romanova, T.Y.: Φ-functions for complex 2D-objects. 4OR (Quart. J. Belg. French Ital. Oper. Res. Soc.) 2, 69–84 (2004)

    Google Scholar 

  115. Teng, H.F., Sun, S.L., Liu, D.Q.: Layout optimization for the objects located within a rotating vessel a three-dimensional packing problem with behavioural constraints. Comput. Oper. Res. 28(6), 521–535 (2001)

    MATH  Google Scholar 

  116. Egeblad, J.: Placement of two- and three-dimensional irregular shapes for inertia moment and balance. In: Morabito R, Arenales MN, Yanasse HH (eds.). Int. Trans. Oper. Res. 16(6), 789–807 (2009) [Special issue on cutting, packing and related problems]

    Google Scholar 

  117. Takadama, K., Tokunaga, F., Shimohara, K.: (2004) Capabilities of a multiagent-based cargo layout system for H-II transfer vehicle. In: 16th IFAC Symposium on Automatic Control in Aerospace (ACA'04), pp. 250–255, St. Petersburg, Russia, 14–18 June 2004

    Google Scholar 

  118. Junqueira, L., et al.: Optimization models for the three-dimensional container loading problem with practical constraints. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  119. Stoyan, Y.G., Romanova, T.: Mathematical models of placement optimisation: two- and three-dimensional problems and applications. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  120. Bussolino, L., Fasano, G., Novelli, A.: The CAST project. In: Ciriani, T., Fasano, G., Gliozzi, S., Tadei, R. (eds.) Operations Research in Space and Air, pp. 13–26. Kluwer, Dordrecht (2003)

    Google Scholar 

  121. Fasano, G., Barrera, M., Lavopa, C., Arguello, L., Steinkopf, M.: Cargo accommodation by interactive engineering: the CAST project. In: 9th international workshop on simulation for european space programmes - SESP 2006- 434950, ESTEC Noordwijk, the Netherlands, 6–8 Nov 2006

    Google Scholar 

  122. Fasano, G.: A multi-level MIP-based heuristic approach for the cargo accommodation of a space vehicle.In: 6th ESICUP Meeting, Valencia, Spain, 25–29 Mar 2009

    Google Scholar 

  123. Fasano, G., Lavopa, C., Negri, D., Vola, M.C., Castellazzo, A.: Packing optimization problems in space engineering. In: SIMAI Biannual Congresses, Turin, June 25–28 (2012)

    Google Scholar 

  124. Fasano, G., Vola, M.C.: Space module on-board stowage optimization by exploiting empty container volumes. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  125. Bandecchi, M., Melton, B., Onagro, F.: Concurrent engineering applied to space mission assessment and design. ESA Bulletin 99, pp. 34–40 (1999)

    Google Scholar 

  126. Ciriani, T.A., Sarlo, L.: Operations research applications in space systems development and operations. In: Ciriani, T., Fasano, G., Gliozzi, S., Tadei, R. (eds.) Operations Research in Space and Air, pp. 3–12. Kluwer, Dordrecht (2003)

    Google Scholar 

  127. Cassioli, A., Schoen, F.: Global optimization of expensive black box problems with a known lower bound. J. Global Optim. (2011) (to appear)

    Google Scholar 

  128. Amata, G.B., Fasano, G., Arcaro, L., Della Croce, F., Norese, M.F., Palamara, S., Tadei, R., Fragnelli, F.: Multidisciplinary Optimisation in Mission Analysis and Design Process. European Space Agency, GSP 1-4487/03/NL/MV, Turin (2004)

    Google Scholar 

  129. Pastrone, D., Casalino, L.: Integrated design-trajectory optimization for hybrid rocket motors. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  130. Nicolescu, G., Mosterman, P.: Model-Based Design for Embedded Systems (Computational Analysis, Synthesis, and Design of Dynamic Systems). CRC, Boca Raton (2009)

    Google Scholar 

  131. Norstrøm, J.G., Cooke, R.M., Bedford, T.: Value of information based design of control software. In: Ciriani, T., Fasano, G., Gliozzi, S., Tadei, R. (eds.) Operations Research in Space and Air, pp. 179–202. Kluwer, Dordrecht (2003)

    Google Scholar 

  132. Edwards, W., Miles, R.F., von Winterfeldt, D. (eds.): Advances in Decision Analysis from Foundations to Applications. Cambridge University Press, Cambridge (2007)

    Google Scholar 

  133. Fasano, G.: Simulation and control of microbial contamination within a manned space system. Technical report M95-MI-AI-0057, Thales Alenia Space Italia, Turin (1996)

    Google Scholar 

  134. Brauer, F., Castillo-Chavez, C.: Mathematical Models in Population Biology and Epidemiology. Springer, Heidelberg (2000)

    Google Scholar 

  135. Mehlem, K.: Optimal magnetic cleanliness modeling of spacecraft. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

  136. Migdalas, A., Pardalos, P.M., Värbrand, P. (eds.): From Local to Global Optimization. Kluwer, Dordrecht (2001)

    MATH  Google Scholar 

  137. Welch, G., Bishop, G.: An introduction to the Kalman filter. SIGGRAPH 2001, Course 8. Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA (2001)

    Google Scholar 

  138. Cramer, E.J., Dennis, J.E., Frank, P.D., Lewis, R.M., Shubin, G.R.: Problem formulation for multidisciplinary optimization. SIAM J. Optim. 4(4), 754–776 (1994)

    MathSciNet  MATH  Google Scholar 

  139. Fasano, G., Lavopa, C., Negri, D., Vola, M.C.: MIP approach for solving the stowage problem on-board the International Space Station. In: 23rd EURO Conference, Bonn, Germany, 5–8 July 2009

    Google Scholar 

  140. Fasano, G., Saia, D., Piras, A.: Columbus stowage optimization by CAST (Cargo Accommodation Support Tool). Acta Astronaut. 67(3), 489–496 (2010)

    Google Scholar 

  141. Fourer, R., Gay, D.M., Kernighan, B.W.: AMPL: A Modeling Language for Mathematical Programming. Brooks/Cole Publishing Company/Cengage Learning, Independence (2002). See also www.ampl.com (2012)

    Google Scholar 

  142. Frontline Systems: Premium Solver Platform Solver Engines. Frontline Systems, Incline Village (2012). See www.solver.com (2012)

    Google Scholar 

  143. Kennedy, J.F.: Speech given at Rice University, Houston. (Kennedy spoke about the subject also on other occasions: cf. e.g. http://www.historyplace.com/speeches/jfk-space.htm, http://www.hark.com/clips/nzpntrdvjl-this-nation-should-land-a-man-on-the-moon. Accessed 12 Sept 1962 (2012)

  144. LINDO Systems: LINGO. LINDO Systems Inc, Chicago (2012). www.lindo.com (2012)

    Google Scholar 

  145. Maximal Software: MPL Modeling System. Maximal Software Inc, Arlington (2012). www.maximal-usa.com (2012)

    Google Scholar 

  146. Paragon Decision Technology: AIMMS. Paragon Decision Technology BV, Haarlem (2006). See www.aimms.com (2012)

    Google Scholar 

  147. TOMLAB Optimization: TOMLAB. TOMLAB Optimization AB, Västerås (2006). www.tomopt.com (2012)

    Google Scholar 

  148. Bertsekas, D.P.: Nonlinear Programming, 2nd edn. Athena Scientific Publishing, Cambridge, MA (1999)

    Google Scholar 

  149. Fasano, G.: The space-module payload accommodation problem: an MIP formulation. In: Ciriani, T.A., Leachman, R.C. (eds.) Optimization in Industry, 2, pp. 33–42. John Wiley & Sons, Chichester (1994)

    Google Scholar 

  150. Boada, J., Prieur, C., Tarbouriech, S., Pittet C., Charbonnel C.: Formation flying control for satellites: anti-windup based approach. In: Fasano, G., Pintér, J.D. (eds.) Modeling and Optimization in Space Engineering. Springer, New York (2013)

    Google Scholar 

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Acknowledgments

First of all, we wish to thank all contributing authors to the present edited volume [11], as well as our coauthors for their contributions to joint work listed in the References. Thanks are also due to M. Parisch and C. Tomatis (Thales Alenia Space) for useful discussions and valuable suggestions regarding the topics reviewed in Sect. 1.3.

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Correspondence to János D. Pintér .

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Fasano, G., Pintér, J.D. (2012). Model Development and Optimization for Space Engineering: Concepts, Tools, Applications, and Perspectives. In: Fasano, G., Pintér, J. (eds) Modeling and Optimization in Space Engineering. Springer Optimization and Its Applications, vol 73. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4469-5_1

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